Proceso de optimización en el diseño de sistema de calefacción solar pasivo

Juan  Giraldo; Juan Pablo  Arango

doi:10.37116/revistaenergia.v16.n2.2020.357

Optimization process in the design of passive solar heating system

Proceso de optimización en el diseño de sistema de calefacción solar pasivo

Published 2020-01-23

https://doi.org/10.37116/revistaenergia.v16.n2.2020.357

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Vol. 16 No. 2 (2020): Revista Técnica "energía", Edición No. 16

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EFICIENCIA ENERGÉTICA

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Optimization process in the design of passive solar heating system. (2020). Revista Técnica "energía", 16(2), 100-110. https://doi.org/10.37116/revistaenergia.v16.n2.2020.357

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https://doi.org/10.37116/revistaenergia.v16.n2.2020.357

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How to Cite

Optimization process in the design of passive solar heating system. (2020). Revista Técnica "energía", 16(2), 100-110. https://doi.org/10.37116/revistaenergia.v16.n2.2020.357

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Juan Giraldo

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https://orcid.org/0000-0003-3425-5549

Juan Pablo Arango

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https://orcid.org/0000-0002-0582-5592

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Juan Giraldo

Nació en Herveo, Colombia en 1993. Recibió su título de Arquitecto de la Universidad Nacional de Colombia sede Manizales en 2015. Es docente investigador de la Facultad de Arquitectura de la Universidad La Gran Colombia en Bogotá, Colombia. Sus campos de investigación están relacionados con el diseño ambientalmente correcto, la arquitectura bioclimática y eficiencia energética.

Juan Pablo Arango

Nació en Medellín, Colombia en 1997. Arquitecto Summa Cum Laude de la Universidad Nacional de Colombia en 2019. Actualmente se encuentra como practicante en Transsolar, Alemania, aplicando sus conocimientos en el ambiente construido.

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Adaptative Thermal Comfort

Passive Solar Heating

Black-box Optimization

Parametric Energy Simulation

The present investigation will determine the optimal design solution of a passive solar collection system that adheres to existing constructions, in order to improve the conditions of indoor hygrothermal comfort, through a parametric work methodology, with case studies in the climate of the Cundiboyacense highlands in Bogota Colombia.

To find the optimal solution for the study area, dynamic thermal simulations using EnergyPlus were integrated with an automated black-box optimization analysis process using the RBFOpt algorithm, which uses advanced machine learning techniques to find optimal solutions with a small number of function evaluations.

The first conclusions of the investigation show the most important variables for the optimal design of the solar collection systems are mainly the width and height of the solar collection system, but not so much its depth, for which the Trombe wall is ideal for the case study climate. In addition, it is possible to improve the conditions of comfort inside the spaces for night use regardless of their orientation, a favorable factor for the purposes of the investigation, which consider homes and constructions in the work area that have all kinds of orientations.

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